In the field of pattern recognition, classifiers are used to classify an object into one of a number of predefined classes or categories. For example, classifiers may be used to classify a loan applicant as either a high risk or a low risk. Other applications for classifiers include speech recognition, face recognition, image processing, and medical diagnosis.
Classifiers are used in image processing to classify pixels or regions in an image into one of a number of predefined classes. For example, a classifier may be used to classify regions in an image of natural scenery into one of a number of classes such as leaves, grass, or sky. In the medical field, classifiers are used to classify regions in images of patients into different types of tissue, for example, abnormal or diseased tissue and normal tissue.
Classification typically involves extracting a set of features of an object called a feature vector. A feature can be any characteristic or property of the object that provides useful information of the object's class. The feature may be in the form of a numeric measurement of a characteristic or property of the object. For example, a feature of a loan applicant may be the applicant's monthly income. A classifier uses the feature vector of the object to classify the object into one of a number of predefined classes or categories.
A classifier can be customized for a particular classification problem by training the classifier to identify particular classes. This usually involves a training phase, in which the classifier is presented with a set of example objects that are representative of known classes. The classifier extracts features of the example objects and learns to associate these features with the known classes of the objects based on association rules. Once the classifier has been trained to identify the classes, the classifier can be used to identify occurrences of these classes in new objects.
In practice, classifiers misclassify objects some of the time. Therefore, there is a need to improve classification accuracy.